# Online automatic code generation for robot swarms: LLMs and self-organizing hierarchy

arXiv: https://arxiv.org/abs/2510.04774 · HTML: https://mlsanity.com/paper/2510.04774/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 3 of its 8 references that are in the map.
- First posted on arXiv 6 Oct 2025.

## Builds on (most cited first, 3 of 3)

- [DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning](https://mlsanity.com/paper/2501.12948/) (2025)
- [LLM2Swarm: Robot Swarms that Responsively Reason, Plan, and Collaborate through LLMs](https://mlsanity.com/paper/2410.11387/) (2024)
- [Self-organizing Nervous Systems for Robot Swarms](https://mlsanity.com/paper/2401.13103/) (2024)

## Built on by (most cited first, 2 of 2)

- [Probing the Prefill: Detecting Code Vulnerabilities via Latent Activations](https://mlsanity.com/paper/2608.16970/) (2026)
- [Auto-HSI: Personalized human control of a robot swarm on demand by using LLMs for online automatic code generation](https://mlsanity.com/paper/2609.16346/) (2026)

## Abstract (arXiv)

Our recently introduced self-organizing nervous system (SoNS) provides robot swarms with 1) ease of behavior design and 2) global estimation of the swarm configuration and its collective environment, facilitating the implementation of online automatic code generation for robot swarms. In a demonstration with 6 real robots and simulation trials with >30 robots, we show that when a SoNS-enhanced robot swarm gets stuck, it can automatically solicit and run code generated by an external LLM on the fly, completing its mission with an 85% success rate.